Thomas Purcell
Assistant Professor Of Chemistry And Biochemistry at University of Arizona
Tucson, Arizona, United States
Summary
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Senior🎓
Top SchoolThomas Purcell is an Assistant Professor of Chemistry and Biochemistry and an Alexander von Humboldt Fellow–trained physical chemist who develops high-throughput workflows and machine learning methods to unravel thermal transport in materials. With a Ph.D. from Northwestern on plasmon–quantum emitter interactions and over a decade of research experience across the Fritz Haber Institute and University of Arizona, he bridges theory, computation, and experiment. He contributes to major open-source materials software—enhancing FHI-aims IO and robustness within the widely used pymatgen library—bringing production-quality parsing, unit handling, and test coverage to computational materials workflows. His work uniquely combines classical and semi-classical modeling with data-driven automation, enabling scalable studies of thermal properties that would be impractical by hand. Based in Tucson, he blends academic leadership with hands-on software engineering to accelerate materials discovery.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Chemistry, Bachelor of Science - BS, Chemistry at New York UniversityNorthwestern University
Github Skills (7)
pymatgen10
science10
python10
materials-informatics10
testing9
data-structure9
data-structures9
Programming languages (4)
Github contributions (5)
materialsproject/pymatgen
Oct 2023 - Mar 2025
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 reviews, 12 PRs, 71 comments in 1 year 4 months
Contributions summary:Thomas primarily focused on enhancing the FHI-aims input/output functionality within the pymatgen library. They implemented FHI-aims IO parsers, including classes for geometry, control, and cube file handling, and integrated them with existing pymatgen data structures. A significant portion of their work involved refactoring and adding tests for the parsers, ensuring their reliability and robustness, while also addressing bug fixes related to the Aims parsers and input sets. The user also addressed stress handling and unit conversions within the FHI-aims output.
moleculespythonscienceelectronic-structurepowers
tpurcell90/atomate2
Oct 2023 - Mar 2025
Contributions:13 reviews, 3 PRs, 88 pushes in 1 year 5 months
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